Functions

Models

BSTModelKit.jl provides a set of tools for constructing and solving S-system BST representations. Models are represented by the BSTModel type, which is a mutable composite type holding information about the model structure and parameters:

BSTModelKit.BSTModel — Type

mutable struct BSTModel <: AbstractBSTModel

Mutable holding structure for the BST model object. This object is used to store all the data that is needed to simulate the model. The object is passed to the evaluate function to simulate the model. A BSTModel object is created using the build function.

Fields

number_of_dynamic_states::Int64: The number of dynamic states in the model.
number_of_static_states::Int64: The number of static states in the model.
list_of_dynamic_species::Array{String,1}: A list of the dynamic species in the model.
list_of_static_species::Array{String,1}: A list of the static species in the model.
list_of_reactions::Array{String,1}: A list of the reactions in the model.
total_species_list::Array{String,1}: A list of all the species in the model.
static_factors_array::Array{Float64,1}: A list of the static factors in the model.
initial_condition_array::Array{Float64,1}: A list of the initial conditions for the dynamic states.
S::Array{Float64,2}: The stoichiometry matrix.
G::Array{Float64,2}: The exponent matrix.
α::Array{Float64,1}: The rate constant vector.

Metadata fields

author::String: The author of the model.
version::String: The version of the model.
date::String: The date the model was created.
description::String: A description of the model.

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Models can be constructed from a variety of file formats in combination with the build function:

BSTModelKit.build — Function

build(path::String) -> BSTModel

This function is used to build a BSTModel object from a model file. The model file can be in one of the following formats: bst, txt, jld2, dat, net, toml. The function will parse the file and build the model object.

Arguments

path::String: The path to the model file.

Returns

A BSTModel object. See the BSTModel documentation for more information on the fields of the model object.

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Once a model instance is constructed, it can be saved to a file or loaded from a file using the savemodel and loadmodel functions:

BSTModelKit.loadmodel — Function

loadmodel(path::String) -> AbstractBSTModel

This function is used to load a BSTModel object from a file. The file can be in one of the following formats: JLD2. The function will load the model object from the file specified by the path argument.

Arguments

path::String: The path to the file where the model object will be loaded from.

Returns

A BSTModel object that was loaded from the file.

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BSTModelKit.savemodel — Function

savemodel(path::String, model::T) -> Bool where T <: AbstractBSTModel

This function is used to save a BSTModel object to a file. The file can be in one of the following formats: JLD2. The function will save the model object to the file specified by the path argument.

Arguments

path::String: The path to the file where the model object will be saved.
model::T: The BSTModel object that will be saved to the file.

Returns

A boolean indicating if the model object was saved successfully.

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Solving

BSTModelKit.evaluate — Function

evaluate(model::BSTModel; tspan::Tuple{Float64,Float64} = (0.0,20.0), Δt::Float64 = 0.01, 
    input::Union{Nothing,Function} = nothing) -> Tuple{Array{Float64,1}, Array{Float64,2}}

This function is used to evaluate the model object that has been built using the build function. The evaluate function will return a tuple with two elements: a vector of time points and a matrix of state values.

Arguments

model::BSTModel: A model object that has been built using the build function.
tspan::Tuple{Float64,Float64}: A tuple that defines the time span for the simulation. The default is (0.0,20.0).
Δt::Float64: The time step for the simulation. The default is 0.01.
input::Union{Nothing,Function}: An optional input function that can be used to drive the simulation. The default is nothing.

Returns

A tuple with two elements:
- Array{Float64,1}: A vector of time points.
- Array{Float64,2}: A matrix of state values.

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BSTModelKit.steadystate — Function

steadystate(model::BSTModel; tspan::Tuple{Float64,Float64} = (0.0,20.0), Δt::Float64 = 0.01, input::Union{Nothing,Function} = nothing) -> Array{Float64,1}

The steadystate function is used to evaluate the steady state of the model object that has been built using the build function.

Arguments

model::BSTModel: A model object that has been built using the build function.
tspan::Tuple{Float64,Float64}: A tuple that defines the time span for the simulation. The default is (0.0,20.0).
Δt::Float64: The time step for the simulation. The default is 0.01.
input::Union{Nothing,Function}: An optional input function that can be used to drive the simulation. The default is nothing.

Returns

A vector of state values that represent the steady state of the system.

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Sensitivity Analysis

BSTModelKit.sobol — Function

sobol(performance::Function, L::Array{Float64,1}, U::Array{Float64,1}; 
    number_of_samples::Int64 = 1000, orders::Array{Int64,1} = [0, 1, 2])

The sobol function is a wrapper around the gsa function that uses the Sobol method to perform a global sensitivity analysis.

Arguments

performance::Function: a function that takes a vector of parameters and returns a scalar performance metric.
L::Array{Float64,1}: a vector of lower bounds for the parameters.
U::Array{Float64,1}: a vector of upper bounds for the parameters.
number_of_samples::Int64: the number of samples to use in the analysis.
orders::Array{Int64,1}: the orders of sensitivity to compute.

Returns

a SobolResult object.

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BSTModelKit.morris — Function

morris(performance::Function, L::Array{Float64,1}, U::Array{Float64,1}; 
    number_of_samples::Int64 = 1000) -> Array{Float64,2}

The morris function is a wrapper around the gsa function that uses the Morris method to perform a global sensitivity analysis.

Arguments

performance::Function: a function that takes a vector of parameters and returns a scalar performance metric.
L::Array{Float64,1}: a vector of lower bounds for the parameters.
U::Array{Float64,1}: a vector of upper bounds for the parameters.
number_of_samples::Int64: the number of samples to use in the analysis.

Returns

a matrix of results where the first column is the mean and the second column is the variance of the sensitivity analysis.

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Utility

Base.indexin — Function

indexin(dd::Dict{String,Any},species_symbol::String; 
    key="total_species_list")::Union{Nothing,Int}

The indexin function is a utility function that returns the index of a species in the total species list of a model.

Arguments

dd::Dict{String,Any}: a dictionary that contains the model data.
species_symbol::String: the symbol of the species to find.
key::String: the key in the dictionary that contains the total species list.

Returns

an integer that represents the index of the species in the total species list, or nothing if the species is not found.

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